Evaluation of Noninvasive Adjuncts for Early Detection of Oral Cancer in Oral Potentially Malignant Disorders and Development of Risk-Based Management Strategies: Protocol for a Prospective Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Oral potentially malignant disorders (OPMDs) constitute the most important precursors of oral cancer. Histopathological examination of a biopsy from a clinically suspicious lesion is still the gold standard for the diagnosis of oral cancer. Adjunctive techniques such as autofluorescence, toluidine blue (TB), and others have been evaluated among high-risk individuals such as chronic tobacco chewers or in patients with suspicious lesions. However, evaluation of these noninvasive adjunctive techniques has not been performed in primary health care settings. Since the first point-of-contact of individuals living in rural and semiurban areas are the primary health care workers, evaluation of these noninvasive adjuncts is likely to assist and strengthen the population-wide oral cancer screening in high-burden countries such as India. OBJECTIVE: This prospective longitudinal study aims to evaluate the noninvasive adjuncts in oral cancer screening in the field settings, specifically in detecting foci of oral cancers in various OPMDs. METHODS: After staff recruitment and training, we shall conduct oral cancer screening camps in the community for the recruitment of individuals with OPMDs after obtaining informed consent. All patients with OPMD shall undergo further screening via autofluorescence and TB staining for detection of lesions suspicious of oral cancer. Sensitivity, specificity, and negative and positive predictive values of these adjunctive techniques (autofluorescence and TB) in the detection of oral cancer shall be calculated using biopsy as the gold standard. In addition, this study will also focus on the validation of the 2022 consensus guidelines on risk-based stratification and appropriate management protocols for the OPMDs at the primary and referral health care centers. Our primary outcome is the diagnostic use of autofluorescence and TB in oral cancer detection among OPMDs as well as the robustness of the risk-based management protocols for these patients. RESULTS: Participant recruitment has been initiated at all sites. Staff recruitment and training in the oral visual examination have been conducted. Procurement of the autofluorescence device is in progress. All the study sites have begun conducting oral screening camps. CONCLUSIONS: The results of this study shall provide robust evidence for the diagnostic use of autofluorescence and TB staining in early oral cancer detection among patients with OPMD. The use of these noninvasive adjuncts by primary health care providers can significantly improve oral cancer screening in our country. The validation of risk-based stratification and management of patients with OPMD shall assist in the refinement of the national guidelines for these interventions. This study has been approved by the respective ethics committee of ICMR-National Institute of Cancer Prevention and Research and the collaborating institutes. The findings of this study shall be disseminated through scientific publications in peer-reviewed journals as well as meetings with the concerned stakeholders at the district and state health departments. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/66285.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".